Overview

Brought to you by YData

Dataset statistics

Number of variables21
Number of observations1340
Missing cells11
Missing cells (%)< 0.1%
Duplicate rows12
Duplicate rows (%)0.9%
Total size in memory220.0 KiB
Average record size in memory168.1 B

Variable types

Text1
Numeric19
Categorical1

Alerts

Dataset has 12 (0.9%) duplicate rowsDuplicates
3P Made is highly overall correlated with 3P% and 1 other fieldsHigh correlation
3P% is highly overall correlated with 3P Made and 1 other fieldsHigh correlation
3PA is highly overall correlated with 3P Made and 3 other fieldsHigh correlation
AST is highly overall correlated with 3PA and 7 other fieldsHigh correlation
BLK is highly overall correlated with DREB and 2 other fieldsHigh correlation
DREB is highly overall correlated with BLK and 10 other fieldsHigh correlation
FG% is highly overall correlated with 3PA and 2 other fieldsHigh correlation
FGA is highly overall correlated with AST and 10 other fieldsHigh correlation
FGM is highly overall correlated with AST and 11 other fieldsHigh correlation
FTA is highly overall correlated with DREB and 10 other fieldsHigh correlation
FTM is highly overall correlated with AST and 11 other fieldsHigh correlation
GP is highly overall correlated with DREB and 9 other fieldsHigh correlation
MIN is highly overall correlated with AST and 11 other fieldsHigh correlation
OREB is highly overall correlated with BLK and 8 other fieldsHigh correlation
PTS is highly overall correlated with AST and 11 other fieldsHigh correlation
REB is highly overall correlated with BLK and 11 other fieldsHigh correlation
STL is highly overall correlated with AST and 8 other fieldsHigh correlation
TOV is highly overall correlated with AST and 10 other fieldsHigh correlation
3P Made has 646 (48.2%) zeros Zeros
3PA has 360 (26.9%) zeros Zeros
3P% has 440 (32.8%) zeros Zeros
BLK has 139 (10.4%) zeros Zeros

Reproduction

Analysis started2024-10-22 07:28:12.135211
Analysis finished2024-10-22 07:29:32.006207
Duration1 minute and 19.87 seconds
Software versionydata-profiling vv4.11.0
Download configurationconfig.json

Variables

Name
Text

Distinct1294
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
2024-10-22T09:29:32.848776image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length12.688806
Min length7

Characters and Unicode

Total characters17003
Distinct characters57
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1265 ?
Unique (%)94.4%

Sample

1st rowBrandon Ingram
2nd rowAndrew Harrison
3rd rowJaKarr Sampson
4th rowMalik Sealy
5th rowMatt Geiger
ValueCountFrequency (%)
williams 36
 
1.3%
chris 33
 
1.2%
smith 32
 
1.2%
johnson 29
 
1.1%
charles 22
 
0.8%
mike 21
 
0.8%
john 20
 
0.7%
brown 19
 
0.7%
jones 19
 
0.7%
anthony 18
 
0.7%
Other values (1372) 2439
90.7%
2024-10-22T09:29:33.674894image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1525
 
9.0%
1348
 
7.9%
r 1285
 
7.6%
n 1284
 
7.6%
a 1229
 
7.2%
o 1078
 
6.3%
i 967
 
5.7%
l 862
 
5.1%
s 750
 
4.4%
t 548
 
3.2%
Other values (47) 6127
36.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 17003
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1525
 
9.0%
1348
 
7.9%
r 1285
 
7.6%
n 1284
 
7.6%
a 1229
 
7.2%
o 1078
 
6.3%
i 967
 
5.7%
l 862
 
5.1%
s 750
 
4.4%
t 548
 
3.2%
Other values (47) 6127
36.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 17003
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1525
 
9.0%
1348
 
7.9%
r 1285
 
7.6%
n 1284
 
7.6%
a 1229
 
7.2%
o 1078
 
6.3%
i 967
 
5.7%
l 862
 
5.1%
s 750
 
4.4%
t 548
 
3.2%
Other values (47) 6127
36.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 17003
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1525
 
9.0%
1348
 
7.9%
r 1285
 
7.6%
n 1284
 
7.6%
a 1229
 
7.2%
o 1078
 
6.3%
i 967
 
5.7%
l 862
 
5.1%
s 750
 
4.4%
t 548
 
3.2%
Other values (47) 6127
36.0%

GP
Real number (ℝ)

High correlation 

Distinct70
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60.414179
Minimum11
Maximum82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-10-22T09:29:33.899343image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile31
Q147
median63
Q377
95-th percentile82
Maximum82
Range71
Interquartile range (IQR)30

Descriptive statistics

Standard deviation17.433992
Coefficient of variation (CV)0.28857451
Kurtosis-0.7857294
Mean60.414179
Median Absolute Deviation (MAD)15
Skewness-0.47774272
Sum80955
Variance303.94409
MonotonicityNot monotonic
2024-10-22T09:29:34.125093image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
82 115
 
8.6%
81 58
 
4.3%
80 56
 
4.2%
79 50
 
3.7%
78 41
 
3.1%
77 35
 
2.6%
76 33
 
2.5%
64 31
 
2.3%
51 29
 
2.2%
75 29
 
2.2%
Other values (60) 863
64.4%
ValueCountFrequency (%)
11 2
 
0.1%
12 2
 
0.1%
14 1
 
0.1%
15 3
0.2%
16 1
 
0.1%
18 3
0.2%
19 4
0.3%
20 2
 
0.1%
21 3
0.2%
22 5
0.4%
ValueCountFrequency (%)
82 115
8.6%
81 58
4.3%
80 56
4.2%
79 50
3.7%
78 41
 
3.1%
77 35
 
2.6%
76 33
 
2.5%
75 29
 
2.2%
74 23
 
1.7%
73 16
 
1.2%

MIN
Real number (ℝ)

High correlation 

Distinct325
Distinct (%)24.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.624627
Minimum3.1
Maximum40.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-10-22T09:29:34.337279image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum3.1
5-th percentile6.8
Q110.875
median16.1
Q322.9
95-th percentile33.8
Maximum40.9
Range37.8
Interquartile range (IQR)12.025

Descriptive statistics

Standard deviation8.3079637
Coefficient of variation (CV)0.47138381
Kurtosis-0.42271657
Mean17.624627
Median Absolute Deviation (MAD)5.8
Skewness0.63225729
Sum23617
Variance69.022261
MonotonicityNot monotonic
2024-10-22T09:29:34.540378image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14.8 13
 
1.0%
8.5 13
 
1.0%
19.8 12
 
0.9%
15.1 12
 
0.9%
10.6 12
 
0.9%
22.6 12
 
0.9%
10.1 11
 
0.8%
15.4 11
 
0.8%
9.2 11
 
0.8%
17 11
 
0.8%
Other values (315) 1222
91.2%
ValueCountFrequency (%)
3.1 1
 
0.1%
4.1 1
 
0.1%
4.2 3
0.2%
4.3 2
0.1%
4.4 1
 
0.1%
4.5 1
 
0.1%
4.6 1
 
0.1%
4.7 3
0.2%
4.8 1
 
0.1%
4.9 1
 
0.1%
ValueCountFrequency (%)
40.9 1
0.1%
40.1 1
0.1%
39.7 1
0.1%
39.6 1
0.1%
39.5 1
0.1%
39.2 1
0.1%
38.6 1
0.1%
38.3 2
0.1%
38 2
0.1%
37.9 1
0.1%

PTS
Real number (ℝ)

High correlation 

Distinct191
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.8014925
Minimum0.7
Maximum28.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-10-22T09:29:34.734308image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.7
5-th percentile2
Q13.7
median5.55
Q38.8
95-th percentile15.905
Maximum28.2
Range27.5
Interquartile range (IQR)5.1

Descriptive statistics

Standard deviation4.3575449
Coefficient of variation (CV)0.64067481
Kurtosis1.9185504
Mean6.8014925
Median Absolute Deviation (MAD)2.35
Skewness1.3882242
Sum9114
Variance18.988198
MonotonicityNot monotonic
2024-10-22T09:29:34.922668image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.7 26
 
1.9%
4.1 26
 
1.9%
4.5 25
 
1.9%
3.3 24
 
1.8%
2.9 24
 
1.8%
3.1 24
 
1.8%
3.8 23
 
1.7%
5.6 23
 
1.7%
3.9 22
 
1.6%
5.3 21
 
1.6%
Other values (181) 1102
82.2%
ValueCountFrequency (%)
0.7 1
 
0.1%
0.9 1
 
0.1%
1 1
 
0.1%
1.1 4
0.3%
1.2 2
 
0.1%
1.3 7
0.5%
1.4 1
 
0.1%
1.5 6
0.4%
1.6 6
0.4%
1.7 6
0.4%
ValueCountFrequency (%)
28.2 1
0.1%
24.3 1
0.1%
23.7 1
0.1%
23.5 1
0.1%
23.4 1
0.1%
22.9 1
0.1%
22.5 1
0.1%
22 1
0.1%
21.9 2
0.1%
21.6 1
0.1%

FGM
Real number (ℝ)

High correlation 

Distinct87
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6291045
Minimum0.3
Maximum10.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-10-22T09:29:35.120407image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile0.8
Q11.4
median2.1
Q33.4
95-th percentile6.1
Maximum10.2
Range9.9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.6835551
Coefficient of variation (CV)0.64035305
Kurtosis1.7089737
Mean2.6291045
Median Absolute Deviation (MAD)0.9
Skewness1.3425443
Sum3523
Variance2.8343577
MonotonicityNot monotonic
2024-10-22T09:29:35.788647image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.8 54
 
4.0%
2 53
 
4.0%
1.5 53
 
4.0%
1.2 52
 
3.9%
1.3 51
 
3.8%
1 50
 
3.7%
2.1 47
 
3.5%
1.6 45
 
3.4%
1.4 44
 
3.3%
1.9 42
 
3.1%
Other values (77) 849
63.4%
ValueCountFrequency (%)
0.3 2
 
0.1%
0.4 5
 
0.4%
0.5 13
 
1.0%
0.6 16
 
1.2%
0.7 26
1.9%
0.8 28
2.1%
0.9 28
2.1%
1 50
3.7%
1.1 38
2.8%
1.2 52
3.9%
ValueCountFrequency (%)
10.2 1
0.1%
9.8 1
0.1%
9 2
0.1%
8.9 1
0.1%
8.8 1
0.1%
8.7 1
0.1%
8.5 1
0.1%
8.4 2
0.1%
8.2 2
0.1%
8 2
0.1%

FGA
Real number (ℝ)

High correlation 

Distinct159
Distinct (%)11.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.8852985
Minimum0.8
Maximum19.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-10-22T09:29:35.967010image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.8
5-th percentile1.9
Q13.3
median4.8
Q37.5
95-th percentile13.5
Maximum19.8
Range19
Interquartile range (IQR)4.2

Descriptive statistics

Standard deviation3.5934885
Coefficient of variation (CV)0.61058729
Kurtosis1.3700298
Mean5.8852985
Median Absolute Deviation (MAD)1.9
Skewness1.2958807
Sum7886.3
Variance12.913159
MonotonicityNot monotonic
2024-10-22T09:29:36.159669image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.1 29
 
2.2%
3.2 28
 
2.1%
3.6 28
 
2.1%
4.4 27
 
2.0%
3.4 27
 
2.0%
2.8 26
 
1.9%
2.6 24
 
1.8%
4.1 23
 
1.7%
4.2 23
 
1.7%
4.3 22
 
1.6%
Other values (149) 1083
80.8%
ValueCountFrequency (%)
0.8 2
 
0.1%
0.9 1
 
0.1%
1 2
 
0.1%
1.2 3
 
0.2%
1.3 6
0.4%
1.4 4
 
0.3%
1.5 5
0.4%
1.6 10
0.7%
1.7 12
0.9%
1.8 12
0.9%
ValueCountFrequency (%)
19.8 2
0.1%
19.7 1
 
0.1%
19.1 1
 
0.1%
18.9 1
 
0.1%
18.7 1
 
0.1%
17.9 2
0.1%
17.6 2
0.1%
17.5 3
0.2%
17.1 1
 
0.1%
16.9 2
0.1%

FG%
Real number (ℝ)

High correlation 

Distinct284
Distinct (%)21.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.169403
Minimum23.8
Maximum73.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-10-22T09:29:36.343345image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum23.8
5-th percentile34.8
Q140.2
median44.1
Q347.9
95-th percentile54.5
Maximum73.7
Range49.9
Interquartile range (IQR)7.7

Descriptive statistics

Standard deviation6.1376789
Coefficient of variation (CV)0.13895771
Kurtosis0.62367084
Mean44.169403
Median Absolute Deviation (MAD)3.8
Skewness0.20847914
Sum59187
Variance37.671102
MonotonicityNot monotonic
2024-10-22T09:29:36.518824image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42.6 15
 
1.1%
41.5 15
 
1.1%
43.9 15
 
1.1%
43 15
 
1.1%
45.5 14
 
1.0%
45.7 13
 
1.0%
44.6 12
 
0.9%
45 12
 
0.9%
45.9 12
 
0.9%
42.9 12
 
0.9%
Other values (274) 1205
89.9%
ValueCountFrequency (%)
23.8 1
0.1%
25 1
0.1%
26.1 1
0.1%
27 1
0.1%
27.7 1
0.1%
29.1 2
0.1%
29.2 2
0.1%
29.4 1
0.1%
29.5 1
0.1%
29.6 1
0.1%
ValueCountFrequency (%)
73.7 1
0.1%
66.2 1
0.1%
66.1 1
0.1%
65.9 1
0.1%
63.3 1
0.1%
61.6 1
0.1%
61.3 1
0.1%
60.8 1
0.1%
60.4 1
0.1%
60 2
0.1%

3P Made
Real number (ℝ)

High correlation  Zeros 

Distinct23
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.24761194
Minimum0
Maximum2.3
Zeros646
Zeros (%)48.2%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-10-22T09:29:36.672048image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.1
Q30.4
95-th percentile1.1
Maximum2.3
Range2.3
Interquartile range (IQR)0.4

Descriptive statistics

Standard deviation0.3836875
Coefficient of variation (CV)1.5495517
Kurtosis4.2921851
Mean0.24761194
Median Absolute Deviation (MAD)0.1
Skewness2.0328154
Sum331.8
Variance0.1472161
MonotonicityNot monotonic
2024-10-22T09:29:36.829090image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 646
48.2%
0.1 189
 
14.1%
0.3 82
 
6.1%
0.2 79
 
5.9%
0.4 71
 
5.3%
0.7 45
 
3.4%
0.6 42
 
3.1%
0.8 39
 
2.9%
0.5 37
 
2.8%
1 20
 
1.5%
Other values (13) 90
 
6.7%
ValueCountFrequency (%)
0 646
48.2%
0.1 189
 
14.1%
0.2 79
 
5.9%
0.3 82
 
6.1%
0.4 71
 
5.3%
0.5 37
 
2.8%
0.6 42
 
3.1%
0.7 45
 
3.4%
0.8 39
 
2.9%
0.9 19
 
1.4%
ValueCountFrequency (%)
2.3 1
 
0.1%
2.1 1
 
0.1%
2 2
 
0.1%
1.9 4
 
0.3%
1.8 4
 
0.3%
1.7 2
 
0.1%
1.6 8
0.6%
1.5 5
0.4%
1.4 8
0.6%
1.3 10
0.7%

3PA
Real number (ℝ)

High correlation  Zeros 

Distinct54
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7791791
Minimum0
Maximum6.5
Zeros360
Zeros (%)26.9%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-10-22T09:29:37.001445image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.3
Q31.2
95-th percentile3.1
Maximum6.5
Range6.5
Interquartile range (IQR)1.2

Descriptive statistics

Standard deviation1.0618474
Coefficient of variation (CV)1.362777
Kurtosis3.2917505
Mean0.7791791
Median Absolute Deviation (MAD)0.3
Skewness1.8124352
Sum1044.1
Variance1.1275199
MonotonicityNot monotonic
2024-10-22T09:29:37.186782image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 360
26.9%
0.1 190
14.2%
0.2 94
 
7.0%
0.3 78
 
5.8%
0.4 52
 
3.9%
0.5 51
 
3.8%
0.6 34
 
2.5%
0.7 31
 
2.3%
1.1 31
 
2.3%
0.8 31
 
2.3%
Other values (44) 388
29.0%
ValueCountFrequency (%)
0 360
26.9%
0.1 190
14.2%
0.2 94
 
7.0%
0.3 78
 
5.8%
0.4 52
 
3.9%
0.5 51
 
3.8%
0.6 34
 
2.5%
0.7 31
 
2.3%
0.8 31
 
2.3%
0.9 28
 
2.1%
ValueCountFrequency (%)
6.5 1
 
0.1%
6.1 1
 
0.1%
6 1
 
0.1%
5.1 1
 
0.1%
4.9 1
 
0.1%
4.8 3
0.2%
4.7 1
 
0.1%
4.6 3
0.2%
4.5 2
0.1%
4.4 1
 
0.1%

3P%
Real number (ℝ)

High correlation  Zeros 

Distinct254
Distinct (%)19.1%
Missing11
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean19.308126
Minimum0
Maximum100
Zeros440
Zeros (%)32.8%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-10-22T09:29:37.383318image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median22.4
Q332.5
95-th percentile40
Maximum100
Range100
Interquartile range (IQR)32.5

Descriptive statistics

Standard deviation16.022916
Coefficient of variation (CV)0.82985351
Kurtosis0.32153442
Mean19.308126
Median Absolute Deviation (MAD)13.3
Skewness0.28987802
Sum25660.5
Variance256.73385
MonotonicityNot monotonic
2024-10-22T09:29:37.572743image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 440
32.8%
33.3 39
 
2.9%
25 34
 
2.5%
20 26
 
1.9%
16.7 24
 
1.8%
28.6 16
 
1.2%
50 15
 
1.1%
22.2 14
 
1.0%
40 14
 
1.0%
11.1 13
 
1.0%
Other values (244) 694
51.8%
ValueCountFrequency (%)
0 440
32.8%
4.3 2
 
0.1%
4.5 1
 
0.1%
5.3 2
 
0.1%
5.9 1
 
0.1%
6.7 1
 
0.1%
7.1 4
 
0.3%
7.7 1
 
0.1%
8 2
 
0.1%
8.3 2
 
0.1%
ValueCountFrequency (%)
100 4
 
0.3%
66.7 1
 
0.1%
51.1 1
 
0.1%
50 15
1.1%
47.7 1
 
0.1%
47.3 1
 
0.1%
46.7 2
 
0.1%
46.4 1
 
0.1%
46.1 1
 
0.1%
44.4 2
 
0.1%

FTM
Real number (ℝ)

High correlation 

Distinct59
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2976866
Minimum0
Maximum7.7
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-10-22T09:29:37.752131image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.3
Q10.6
median1
Q31.6
95-th percentile3.3
Maximum7.7
Range7.7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.98724609
Coefficient of variation (CV)0.76077391
Kurtosis5.3508009
Mean1.2976866
Median Absolute Deviation (MAD)0.5
Skewness1.9419992
Sum1738.9
Variance0.97465484
MonotonicityNot monotonic
2024-10-22T09:29:37.952574image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.5 97
 
7.2%
0.7 90
 
6.7%
0.8 89
 
6.6%
0.9 86
 
6.4%
1 81
 
6.0%
0.6 79
 
5.9%
0.4 71
 
5.3%
1.1 68
 
5.1%
1.2 56
 
4.2%
1.3 56
 
4.2%
Other values (49) 567
42.3%
ValueCountFrequency (%)
0 1
 
0.1%
0.1 15
 
1.1%
0.2 37
 
2.8%
0.3 47
3.5%
0.4 71
5.3%
0.5 97
7.2%
0.6 79
5.9%
0.7 90
6.7%
0.8 89
6.6%
0.9 86
6.4%
ValueCountFrequency (%)
7.7 1
 
0.1%
7.5 1
 
0.1%
6.3 1
 
0.1%
6 1
 
0.1%
5.7 1
 
0.1%
5.4 2
0.1%
5.3 2
0.1%
5.2 1
 
0.1%
5.1 1
 
0.1%
5 4
0.3%

FTA
Real number (ℝ)

High correlation 

Distinct76
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8219403
Minimum0
Maximum10.2
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-10-22T09:29:38.160998image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.4
Q10.9
median1.5
Q32.3
95-th percentile4.605
Maximum10.2
Range10.2
Interquartile range (IQR)1.4

Descriptive statistics

Standard deviation1.3229843
Coefficient of variation (CV)0.72614032
Kurtosis4.8010762
Mean1.8219403
Median Absolute Deviation (MAD)0.7
Skewness1.8444816
Sum2441.4
Variance1.7502875
MonotonicityNot monotonic
2024-10-22T09:29:38.354684image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.8 73
 
5.4%
1 67
 
5.0%
1.2 66
 
4.9%
1.3 65
 
4.9%
0.7 64
 
4.8%
1.6 56
 
4.2%
0.9 56
 
4.2%
1.1 55
 
4.1%
1.4 51
 
3.8%
1.5 47
 
3.5%
Other values (66) 740
55.2%
ValueCountFrequency (%)
0 1
 
0.1%
0.1 2
 
0.1%
0.2 13
 
1.0%
0.3 27
 
2.0%
0.4 33
2.5%
0.5 40
3.0%
0.6 46
3.4%
0.7 64
4.8%
0.8 73
5.4%
0.9 56
4.2%
ValueCountFrequency (%)
10.2 1
0.1%
9.1 1
0.1%
8.9 1
0.1%
8.5 1
0.1%
8.1 1
0.1%
7.6 1
0.1%
7.3 1
0.1%
7.2 2
0.1%
6.9 1
0.1%
6.8 1
0.1%

FT%
Real number (ℝ)

Distinct383
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean70.300299
Minimum0
Maximum100
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-10-22T09:29:38.560689image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile50.685
Q164.7
median71.25
Q377.6
95-th percentile85.1
Maximum100
Range100
Interquartile range (IQR)12.9

Descriptive statistics

Standard deviation10.578479
Coefficient of variation (CV)0.1504756
Kurtosis2.0387272
Mean70.300299
Median Absolute Deviation (MAD)6.45
Skewness-0.76786256
Sum94202.4
Variance111.90423
MonotonicityNot monotonic
2024-10-22T09:29:38.929712image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
66.7 29
 
2.2%
75 21
 
1.6%
50 18
 
1.3%
72.7 14
 
1.0%
80 13
 
1.0%
83.3 11
 
0.8%
72.2 10
 
0.7%
81 10
 
0.7%
73.7 10
 
0.7%
78.6 10
 
0.7%
Other values (373) 1194
89.1%
ValueCountFrequency (%)
0 1
0.1%
28.6 1
0.1%
29.6 1
0.1%
31.3 2
0.1%
33.3 1
0.1%
35 1
0.1%
35.3 1
0.1%
37.1 1
0.1%
37.5 1
0.1%
38.4 1
0.1%
ValueCountFrequency (%)
100 5
0.4%
94.1 1
 
0.1%
93.8 1
 
0.1%
92.9 1
 
0.1%
92.6 1
 
0.1%
92.3 1
 
0.1%
91.7 1
 
0.1%
91.2 1
 
0.1%
90.9 1
 
0.1%
90.5 2
 
0.1%

OREB
Real number (ℝ)

High correlation 

Distinct44
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.009403
Minimum0
Maximum5.3
Zeros4
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-10-22T09:29:39.199535image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.2
Q10.4
median0.8
Q31.4
95-th percentile2.5
Maximum5.3
Range5.3
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.77711936
Coefficient of variation (CV)0.76988019
Kurtosis2.4833531
Mean1.009403
Median Absolute Deviation (MAD)0.4
Skewness1.4395836
Sum1352.6
Variance0.60391451
MonotonicityNot monotonic
2024-10-22T09:29:39.432668image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0.3 111
 
8.3%
0.5 109
 
8.1%
0.4 98
 
7.3%
0.6 96
 
7.2%
0.7 92
 
6.9%
0.2 92
 
6.9%
0.8 79
 
5.9%
1 64
 
4.8%
1.1 58
 
4.3%
0.9 51
 
3.8%
Other values (34) 490
36.6%
ValueCountFrequency (%)
0 4
 
0.3%
0.1 43
 
3.2%
0.2 92
6.9%
0.3 111
8.3%
0.4 98
7.3%
0.5 109
8.1%
0.6 96
7.2%
0.7 92
6.9%
0.8 79
5.9%
0.9 51
3.8%
ValueCountFrequency (%)
5.3 1
 
0.1%
4.3 2
0.1%
4.2 3
0.2%
4 2
0.1%
3.9 2
0.1%
3.8 1
 
0.1%
3.7 4
0.3%
3.6 2
0.1%
3.5 2
0.1%
3.4 4
0.3%

DREB
Real number (ℝ)

High correlation 

Distinct74
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0257463
Minimum0.2
Maximum9.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-10-22T09:29:39.651797image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile0.5
Q11
median1.7
Q32.6
95-th percentile4.7
Maximum9.6
Range9.4
Interquartile range (IQR)1.6

Descriptive statistics

Standard deviation1.3600075
Coefficient of variation (CV)0.67136123
Kurtosis2.9029176
Mean2.0257463
Median Absolute Deviation (MAD)0.8
Skewness1.4886814
Sum2714.5
Variance1.8496204
MonotonicityNot monotonic
2024-10-22T09:29:39.869024image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.9 60
 
4.5%
1.1 59
 
4.4%
0.7 59
 
4.4%
0.8 59
 
4.4%
1.3 57
 
4.3%
1 51
 
3.8%
1.2 50
 
3.7%
1.7 49
 
3.7%
0.6 48
 
3.6%
1.8 45
 
3.4%
Other values (64) 803
59.9%
ValueCountFrequency (%)
0.2 3
 
0.2%
0.3 11
 
0.8%
0.4 29
2.2%
0.5 31
2.3%
0.6 48
3.6%
0.7 59
4.4%
0.8 59
4.4%
0.9 60
4.5%
1 51
3.8%
1.1 59
4.4%
ValueCountFrequency (%)
9.6 1
0.1%
8.8 1
0.1%
8.3 1
0.1%
8 1
0.1%
7.7 1
0.1%
7.6 1
0.1%
7.1 1
0.1%
7 2
0.1%
6.9 2
0.1%
6.8 1
0.1%

REB
Real number (ℝ)

High correlation 

Distinct101
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0344776
Minimum0.3
Maximum13.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-10-22T09:29:40.068953image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile0.8
Q11.5
median2.5
Q34
95-th percentile7.4
Maximum13.9
Range13.6
Interquartile range (IQR)2.5

Descriptive statistics

Standard deviation2.057774
Coefficient of variation (CV)0.67813123
Kurtosis2.7007598
Mean3.0344776
Median Absolute Deviation (MAD)1.1
Skewness1.4817363
Sum4066.2
Variance4.234434
MonotonicityNot monotonic
2024-10-22T09:29:40.283199image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.2 48
 
3.6%
1.5 47
 
3.5%
1.3 42
 
3.1%
1.9 42
 
3.1%
2 41
 
3.1%
1.7 39
 
2.9%
1.1 35
 
2.6%
2.1 34
 
2.5%
2.9 34
 
2.5%
1.6 34
 
2.5%
Other values (91) 944
70.4%
ValueCountFrequency (%)
0.3 2
 
0.1%
0.4 5
 
0.4%
0.5 6
 
0.4%
0.6 15
 
1.1%
0.7 27
2.0%
0.8 30
2.2%
0.9 33
2.5%
1 30
2.2%
1.1 35
2.6%
1.2 48
3.6%
ValueCountFrequency (%)
13.9 1
 
0.1%
12.3 1
 
0.1%
12.1 2
0.1%
12 1
 
0.1%
11.1 1
 
0.1%
11 2
0.1%
10.9 1
 
0.1%
10.6 2
0.1%
10.5 1
 
0.1%
10.3 3
0.2%

AST
Real number (ℝ)

High correlation 

Distinct77
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5505224
Minimum0
Maximum10.6
Zeros4
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-10-22T09:29:40.488680image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.2
Q10.6
median1.1
Q32
95-th percentile4.405
Maximum10.6
Range10.6
Interquartile range (IQR)1.4

Descriptive statistics

Standard deviation1.4711692
Coefficient of variation (CV)0.94882164
Kurtosis5.7489537
Mean1.5505224
Median Absolute Deviation (MAD)0.6
Skewness2.1328171
Sum2077.7
Variance2.1643388
MonotonicityNot monotonic
2024-10-22T09:29:40.688596image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.5 84
 
6.3%
0.4 80
 
6.0%
0.3 79
 
5.9%
0.8 73
 
5.4%
0.6 72
 
5.4%
0.7 72
 
5.4%
0.2 62
 
4.6%
1.2 58
 
4.3%
1 56
 
4.2%
0.9 56
 
4.2%
Other values (67) 648
48.4%
ValueCountFrequency (%)
0 4
 
0.3%
0.1 18
 
1.3%
0.2 62
4.6%
0.3 79
5.9%
0.4 80
6.0%
0.5 84
6.3%
0.6 72
5.4%
0.7 72
5.4%
0.8 73
5.4%
0.9 56
4.2%
ValueCountFrequency (%)
10.6 1
 
0.1%
9.3 1
 
0.1%
8.7 2
0.1%
8.3 2
0.1%
8.2 2
0.1%
8.1 1
 
0.1%
7.8 3
0.2%
7.7 1
 
0.1%
7.6 1
 
0.1%
7.5 1
 
0.1%

STL
Real number (ℝ)

High correlation 

Distinct26
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.61850746
Minimum0
Maximum2.5
Zeros4
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-10-22T09:29:40.856434image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1
Q10.3
median0.5
Q30.8
95-th percentile1.5
Maximum2.5
Range2.5
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation0.40975868
Coefficient of variation (CV)0.66249594
Kurtosis2.2466673
Mean0.61850746
Median Absolute Deviation (MAD)0.2
Skewness1.3647996
Sum828.8
Variance0.16790218
MonotonicityNot monotonic
2024-10-22T09:29:41.017277image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0.3 195
14.6%
0.4 165
12.3%
0.6 142
10.6%
0.5 138
10.3%
0.2 133
9.9%
0.7 113
8.4%
0.8 87
6.5%
0.1 65
 
4.9%
1 60
 
4.5%
0.9 57
 
4.3%
Other values (16) 185
13.8%
ValueCountFrequency (%)
0 4
 
0.3%
0.1 65
 
4.9%
0.2 133
9.9%
0.3 195
14.6%
0.4 165
12.3%
0.5 138
10.3%
0.6 142
10.6%
0.7 113
8.4%
0.8 87
6.5%
0.9 57
 
4.3%
ValueCountFrequency (%)
2.5 3
 
0.2%
2.4 1
 
0.1%
2.3 1
 
0.1%
2.2 1
 
0.1%
2.1 4
 
0.3%
2 4
 
0.3%
1.9 7
 
0.5%
1.8 9
0.7%
1.7 9
0.7%
1.6 18
1.3%

BLK
Real number (ℝ)

High correlation  Zeros 

Distinct28
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.36858209
Minimum0
Maximum3.9
Zeros139
Zeros (%)10.4%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-10-22T09:29:41.172460image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.1
median0.2
Q30.5
95-th percentile1.205
Maximum3.9
Range3.9
Interquartile range (IQR)0.4

Descriptive statistics

Standard deviation0.4290491
Coefficient of variation (CV)1.164053
Kurtosis12.220561
Mean0.36858209
Median Absolute Deviation (MAD)0.1
Skewness2.8041519
Sum493.9
Variance0.18408313
MonotonicityNot monotonic
2024-10-22T09:29:41.347241image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.1 368
27.5%
0.2 203
15.1%
0.3 182
13.6%
0 139
 
10.4%
0.4 88
 
6.6%
0.5 79
 
5.9%
0.6 60
 
4.5%
0.8 44
 
3.3%
0.7 40
 
3.0%
1.1 23
 
1.7%
Other values (18) 114
 
8.5%
ValueCountFrequency (%)
0 139
 
10.4%
0.1 368
27.5%
0.2 203
15.1%
0.3 182
13.6%
0.4 88
 
6.6%
0.5 79
 
5.9%
0.6 60
 
4.5%
0.7 40
 
3.0%
0.8 44
 
3.3%
0.9 22
 
1.6%
ValueCountFrequency (%)
3.9 1
 
0.1%
3.5 2
 
0.1%
3.4 1
 
0.1%
2.7 1
 
0.1%
2.6 1
 
0.1%
2.4 1
 
0.1%
2.2 2
 
0.1%
2.1 3
0.2%
1.9 3
0.2%
1.8 7
0.5%

TOV
Real number (ℝ)

High correlation 

Distinct41
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1935821
Minimum0.1
Maximum4.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-10-22T09:29:41.531526image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.4
Q10.7
median1
Q31.5
95-th percentile2.705
Maximum4.4
Range4.3
Interquartile range (IQR)0.8

Descriptive statistics

Standard deviation0.72254054
Coefficient of variation (CV)0.60535471
Kurtosis1.8866312
Mean1.1935821
Median Absolute Deviation (MAD)0.4
Skewness1.3407407
Sum1599.4
Variance0.52206483
MonotonicityNot monotonic
2024-10-22T09:29:41.699635image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0.8 114
 
8.5%
0.9 105
 
7.8%
0.6 105
 
7.8%
0.7 103
 
7.7%
0.5 83
 
6.2%
1 81
 
6.0%
1.1 78
 
5.8%
1.2 67
 
5.0%
0.4 64
 
4.8%
1.3 62
 
4.6%
Other values (31) 478
35.7%
ValueCountFrequency (%)
0.1 9
 
0.7%
0.2 7
 
0.5%
0.3 37
 
2.8%
0.4 64
4.8%
0.5 83
6.2%
0.6 105
7.8%
0.7 103
7.7%
0.8 114
8.5%
0.9 105
7.8%
1 81
6.0%
ValueCountFrequency (%)
4.4 1
 
0.1%
4.2 2
 
0.1%
4 1
 
0.1%
3.9 2
 
0.1%
3.8 3
 
0.2%
3.6 3
 
0.2%
3.5 4
0.3%
3.4 8
0.6%
3.3 4
0.3%
3.2 4
0.3%

TARGET_5Yrs
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
1.0
831 
0.0
509 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters4020
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 831
62.0%
0.0 509
38.0%

Length

2024-10-22T09:29:41.870832image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-22T09:29:42.026538image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
1.0 831
62.0%
0.0 509
38.0%

Most occurring characters

ValueCountFrequency (%)
0 1849
46.0%
. 1340
33.3%
1 831
20.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4020
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 1849
46.0%
. 1340
33.3%
1 831
20.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4020
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 1849
46.0%
. 1340
33.3%
1 831
20.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4020
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 1849
46.0%
. 1340
33.3%
1 831
20.7%

Interactions

2024-10-22T09:29:27.509526image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:15.642500image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:20.202946image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:24.477958image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:32.686934image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:36.381398image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:40.589685image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:44.433227image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:47.525849image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:51.214178image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:54.649399image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:58.630888image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:02.354803image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:06.738495image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:10.392097image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:13.922763image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:17.598835image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:20.930935image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:24.135059image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:27.761253image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:15.963181image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:20.368211image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:24.697740image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:32.851562image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:36.630778image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:40.764339image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:44.587341image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:47.705267image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:51.411046image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:54.871215image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:58.815355image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:02.525327image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:06.962801image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:10.574083image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:14.142309image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:17.830013image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:21.099840image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:24.303688image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:27.945689image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:16.324823image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:20.548562image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:24.876374image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:33.015103image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:36.814276image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:40.943295image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:44.740559image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:47.874151image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:51.715946image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:55.029483image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:58.992345image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:02.697881image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:07.121426image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:10.761115image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:14.357273image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:17.998382image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:21.262766image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:24.472644image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:28.126051image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:16.514692image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:20.761256image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:25.017245image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:33.230112image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:36.989210image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:41.111743image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:44.873590image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:48.037261image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:51.903801image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:55.181498image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:59.156682image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:02.988145image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:07.339333image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:10.939075image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:14.524588image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:18.155182image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:21.408165image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:24.707800image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:28.302467image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:16.764753image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:20.959930image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:25.250980image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:33.393829image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:37.191002image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:41.267402image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:45.013029image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:48.316912image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:52.111740image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:55.320920image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:59.332789image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:03.291199image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:07.583556image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:11.141537image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:15.089955image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:18.305970image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:21.629835image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:24.865514image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:28.495309image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:17.046343image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:21.176115image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:25.427410image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:33.555105image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:37.388822image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:41.481745image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:45.248185image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:48.502199image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:52.325906image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:55.475620image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:59.642701image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:03.554614image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:07.832613image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:11.368139image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:15.253496image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:18.487996image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:21.807952image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:25.042248image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:28.647033image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:17.256168image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:21.372373image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:25.751237image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:33.699896image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:37.565810image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:41.778743image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:45.389567image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:48.665854image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:52.504014image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:55.616974image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:59.842997image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:03.878373image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:08.093004image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:11.521003image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:15.388479image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:18.692268image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:21.953908image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:25.194460image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:28.877260image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:17.410943image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:21.562206image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:25.918183image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:33.900199image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:37.880958image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:41.954544image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:45.521105image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:48.800611image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:52.701391image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:55.891701image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:00.047507image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:04.057543image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:08.256855image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:11.670037image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:15.543876image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:18.858140image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:22.103306image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:25.376465image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:29.069590image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:17.587496image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:21.715855image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:30.619952image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:34.190632image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:38.134908image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:42.139609image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:45.669354image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:48.962412image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:52.951551image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:56.064571image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:00.261892image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:04.248986image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:08.428272image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:11.857319image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:15.769605image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:19.023669image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:22.262728image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:25.550478image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:29.264811image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:17.748444image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:21.849444image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:30.846199image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:34.362245image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:38.429167image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:42.293005image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:45.816087image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:49.108750image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:53.113305image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:56.554315image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:00.428546image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:04.482178image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:08.574807image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:12.036319image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:15.928022image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:19.175102image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:22.412583image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:25.778911image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:29.515135image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:17.932549image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:21.996811image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:31.092357image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:34.547221image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:38.661962image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:42.812243image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:45.987957image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:49.344644image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:53.309702image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:56.702621image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:00.629983image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:04.706349image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:08.743280image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:12.334436image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:16.098008image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:19.345751image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:22.655171image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:25.963703image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:29.728385image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:18.171533image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:22.393341image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:31.269981image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:34.704042image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:38.894915image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:42.935904image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:46.193494image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:49.495237image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:53.456237image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:56.849473image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:00.926186image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:05.132987image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:08.890951image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:12.513278image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:16.244664image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:19.497274image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:22.810489image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:26.120616image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:29.968908image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:18.365406image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:23.008443image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:31.442660image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:34.875607image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:39.112628image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:43.181234image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:46.339838image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:49.691934image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:53.592490image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:56.994292image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:01.088641image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:05.357507image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:09.133104image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:12.683999image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:16.395549image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:19.734950image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:22.968989image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:26.277537image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:30.267599image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:18.532582image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:23.286296image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:31.597054image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:35.069560image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:39.400870image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:43.368617image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:46.489161image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:49.870998image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:53.727498image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:57.216428image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:01.270245image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:05.542752image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:09.275634image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:12.863820image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:16.547425image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:19.895675image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:23.119137image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:26.430359image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:30.465322image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:18.693335image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:23.467078image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:31.768614image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:35.309730image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:39.589368image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:43.533854image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:46.640924image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:50.052847image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:53.935633image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:57.497882image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:01.425321image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:05.736091image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:09.434741image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:13.026698image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:16.782797image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:20.056127image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:23.273319image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:26.637620image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:30.631615image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:18.875846image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:23.670408image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:31.976320image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:35.495412image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:39.798127image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:43.683079image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:46.790337image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:50.335617image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:54.086569image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:57.719150image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:01.597205image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:06.031018image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:09.615472image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:13.296514image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:16.948878image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:20.215746image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:23.429158image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:26.829883image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:30.776411image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:19.231322image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:23.941170image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:32.197896image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:35.722373image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:39.979001image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:43.819657image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:46.959592image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:50.646639image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:54.237639image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:57.896968image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:01.837595image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:06.210942image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:09.783514image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:13.450116image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:17.111722image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:20.363055image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:23.655936image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:26.997236image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:30.918196image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:19.450300image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:24.172076image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:32.369331image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:35.943614image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:40.184868image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:43.964481image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:47.175407image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:50.843996image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:54.383244image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:58.080984image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:02.015418image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:06.381877image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:09.953465image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:13.606238image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:17.274800image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:20.608405image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:23.813302image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:27.160760image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:31.073065image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:20.026005image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:24.329322image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:32.541855image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:36.161394image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:40.367668image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:44.268211image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:47.368649image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:51.034319image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:54.528784image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:28:58.422741image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:02.207312image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:06.572660image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:10.244856image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:13.780675image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:17.453555image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:20.789122image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:23.985119image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-22T09:29:27.351265image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Correlations

2024-10-22T09:29:42.156111image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
3P Made3P%3PAASTBLKDREBFG%FGAFGMFT%FTAFTMGPMINOREBPTSREBSTLTARGET_5YrsTOV
3P Made1.0000.7910.9390.434-0.247-0.042-0.4600.3310.2150.382-0.0150.0620.0320.284-0.3580.261-0.1540.3070.0900.188
3P%0.7911.0000.7730.355-0.248-0.101-0.3470.2400.1530.362-0.0400.0300.0430.185-0.3260.192-0.1860.2320.0550.121
3PA0.9390.7731.0000.501-0.297-0.083-0.5080.3620.2340.4190.0010.0860.0420.290-0.3850.278-0.1920.3600.0810.221
AST0.4340.3550.5011.000-0.1110.218-0.1410.6460.5770.3790.4390.5040.4410.652-0.0490.5980.1350.7460.1550.755
BLK-0.247-0.248-0.297-0.1111.0000.7040.4520.3250.401-0.2290.4420.3800.3090.4300.7090.3870.7360.1950.2040.249
DREB-0.042-0.101-0.0830.2180.7041.0000.4500.6600.718-0.0330.6790.6430.5280.7860.7930.7110.9740.4790.2870.560
FG%-0.460-0.347-0.508-0.1410.4520.4501.0000.1730.370-0.1660.3720.3190.3080.2440.5860.3270.5220.0840.2810.148
FGA0.3310.2400.3620.6460.3250.6600.1731.0000.9740.3030.7610.7970.5990.9170.4720.9760.6280.7260.2980.816
FGM0.2150.1530.2340.5770.4010.7180.3700.9741.0000.2480.8010.8220.6310.9150.5710.9900.7040.7000.3370.800
FT%0.3820.3620.4190.379-0.229-0.033-0.1660.3030.2481.0000.1020.2830.1800.238-0.2020.288-0.0930.2190.1220.212
FTA-0.015-0.0400.0010.4390.4420.6790.3720.7610.8010.1021.0000.9760.5640.7730.6260.8420.6960.6090.3070.764
FTM0.0620.0300.0860.5040.3800.6430.3190.7970.8220.2830.9761.0000.5810.7930.5560.8700.6460.6310.3070.779
GP0.0320.0430.0420.4410.3090.5280.3080.5990.6310.1800.5640.5811.0000.6420.4220.6300.5180.5160.3860.593
MIN0.2840.1850.2900.6520.4300.7860.2440.9170.9150.2380.7730.7930.6421.0000.5470.9250.7410.7830.3060.810
OREB-0.358-0.326-0.385-0.0490.7090.7930.5860.4720.571-0.2020.6260.5560.4220.5471.0000.5460.9060.2970.2940.373
PTS0.2610.1920.2780.5980.3870.7110.3270.9760.9900.2880.8420.8700.6300.9250.5461.0000.6900.7170.3310.816
REB-0.154-0.186-0.1920.1350.7360.9740.5220.6280.704-0.0930.6960.6460.5180.7410.9060.6901.0000.4410.2990.520
STL0.3070.2320.3600.7460.1950.4790.0840.7260.7000.2190.6090.6310.5160.7830.2970.7170.4411.0000.2260.734
TARGET_5Yrs0.0900.0550.0810.1550.2040.2870.2810.2980.3370.1220.3070.3070.3860.3060.2940.3310.2990.2261.0000.273
TOV0.1880.1210.2210.7550.2490.5600.1480.8160.8000.2120.7640.7790.5930.8100.3730.8160.5200.7340.2731.000

Missing values

2024-10-22T09:29:31.375925image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-10-22T09:29:31.805426image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

NameGPMINPTSFGMFGAFG%3P Made3PA3P%FTMFTAFT%OREBDREBREBASTSTLBLKTOVTARGET_5Yrs
0Brandon Ingram3627.47.42.67.634.70.52.125.01.62.369.90.73.44.11.90.40.41.30.0
1Andrew Harrison3526.97.22.06.729.60.72.823.52.63.476.50.52.02.43.71.10.51.60.0
2JaKarr Sampson7415.35.22.04.742.20.41.724.40.91.367.00.51.72.21.00.50.31.00.0
3Malik Sealy5811.65.72.35.542.60.10.522.60.91.368.91.00.91.90.80.60.11.01.0
4Matt Geiger4811.54.51.63.052.40.00.10.01.31.967.41.01.52.50.30.30.40.81.0
5Tony Bennett7511.43.71.53.542.30.31.132.50.40.573.20.20.70.81.80.40.00.70.0
6Don MacLean6210.96.62.55.843.50.00.150.01.51.881.10.51.42.00.60.20.10.71.0
7Tracy Murray4810.35.72.35.441.50.41.530.00.70.887.50.80.91.70.20.20.10.71.0
8Duane Cooper659.92.41.02.439.20.10.523.30.40.571.40.20.60.82.30.30.01.10.0
9Dave Johnson428.53.71.43.538.30.10.321.41.01.467.80.40.71.10.30.20.00.70.0
NameGPMINPTSFGMFGAFG%3P Made3PA3P%FTMFTAFT%OREBDREBREBASTSTLBLKTOVTARGET_5Yrs
1330Adam Keefe8218.96.62.34.650.00.00.00.02.02.970.02.13.25.31.00.70.21.21.0
1331Lee Mayberry8218.35.22.14.645.60.51.339.10.50.857.40.31.11.43.30.70.11.01.0
1332Hubert Davis5016.35.42.25.043.80.10.431.60.91.179.60.30.91.11.70.40.10.91.0
1333Byron Houston7916.15.31.84.144.60.00.128.61.62.566.51.52.54.00.90.60.51.10.0
1334Chris Smith8015.84.31.63.643.30.00.214.31.21.579.20.40.81.22.50.60.20.80.0
1335Chris Smith8015.84.31.63.643.30.00.214.31.21.579.20.40.81.22.50.60.20.80.0
1336Brent Price6812.63.91.54.135.80.10.716.70.81.079.40.41.11.52.30.80.01.31.0
1337Marlon Maxey4312.15.42.23.955.00.00.00.01.01.664.31.52.33.80.30.30.40.90.0
1338Litterial Green5212.04.51.73.843.90.00.210.01.21.862.50.20.40.72.20.40.10.81.0
1339Jon Barry4711.74.41.64.436.90.41.333.30.71.067.30.20.70.91.40.70.10.91.0

Duplicate rows

Most frequently occurring

NameGPMINPTSFGMFGAFG%3P Made3PA3P%FTMFTAFT%OREBDREBREBASTSTLBLKTOVTARGET_5Yrs# duplicates
0Charles Jones2916.43.71.34.231.70.72.131.10.40.850.00.31.11.41.40.60.21.00.02
1Charles Jones7820.18.43.05.852.00.00.10.02.33.664.81.83.35.11.60.60.81.80.02
2Charles Smith348.63.51.43.739.20.41.431.90.20.354.50.40.40.80.60.30.20.81.02
3Charles Smith608.72.91.02.244.40.00.10.00.91.369.70.20.91.21.70.60.10.61.02
4Charles Smith7130.416.36.112.449.50.00.00.04.05.572.52.44.16.51.51.01.32.11.02
5Chris Smith8015.84.31.63.643.30.00.214.31.21.579.20.40.81.22.50.60.20.80.02
6Eddie Johnson7420.59.34.08.745.90.00.19.11.32.066.41.72.64.41.50.70.21.31.02
7Gerald Henderson438.32.60.92.435.60.10.421.10.81.174.50.30.91.30.30.20.20.31.02
8Ken Johnson6412.74.11.83.352.80.00.0NaN0.61.343.51.42.43.80.30.20.30.90.02
9Marcus Williams7916.66.82.66.739.50.62.128.20.91.184.70.41.72.13.30.40.01.80.02